In the sensors field the active sensing material frequently needs a controlled temperature in order to work properly. In microsystems technology, micro-machined hotplates represent a platform consisting of a thin suspended membrane where the sensing material can be deposited, usually integrating electrical stimuli and temperature readout. The micro-hotplate ensures a series of advantages such as miniaturized size, fast response, high sensitivity, low power consumption and selectivity for chemical sensing. This work compares the coplanar and the buried approach for the micro-hotplate heaters design with the aim to optimize the fabrication process and to propose a guideline for the choice of the suitable design with respect to the applications. In particular, robust Finite Element Method (FEM) models are set up in order to predict the electrical and thermal behavior of the micro-hotplates. The multiphysics approach used for the simulation allows to match as close as possible the actual device to the predictive model: geometries, materials, physics have been carefully linked to the fabricated devices to obtain the best possible accuracy. The materials involved in the fabrication process are accurately selected in order to improve the yield of the process and the performance of the devices. The fabricated micro-hotplates are able to warm the active region up to 400 °C (with a corresponding power consumption equal to 250 mW @ 400 °C) with a uniform temperature distribution in the buried micro-hotplate and a controlled temperature gradient in the coplanar one. A response time of about 70 ms was obtained on the virtual model, which perfectly agrees with the one measured on the fabricated device. Besides morphological, electrical and thermal characterizations, this work includes reliability tests in static and dynamic modes.
Modeling, Fabrication and Testing of a Customizable Micromachined Hotplate for Sensor Applications / Tommasi, Alessio; Cocuzza, Matteo; Perrone, Denis; Pirri, Candido Fabrizio; Mosca, Roberto; Villani, Marco; Delmonte, Nicola; Zappettini, Andrea; Calestani, Davide; Marasso, Simone Luigi. - In: SENSORS. - ISSN 1424-8220. - 17:1(2017), pp. 1-18. [10.3390/s17010062]